The optimization of the inverted occulter of the Solar Orbiter/METIS coronagraph/spectrometer
Bibliographic record
Abstract
The coronagraph/spectrometer METIS (Multi Element Telescope for Imaging and Spectroscopy), selected to fly aboard the Solar Orbiter ESA/NASA mission, is conceived to perform imaging (in visible, UV and EUV) and spectroscopy (in EUV) of the solar corona. It is an integrated instrument suite located on a single optical bench and sharing a unique aperture on the satellite heat shield. As every coronagraph, METIS is highly demanding in terms of stray light suppression. In order to meet the strict thermal requirements of Solar Orbiter, METIS optical design has been optimized by moving the entrance pupil at the level of the external occulter on the S/C thermal shield, thus reducing the size of the external aperture. The scheme is based on an inverted external-occulter (IEO). The IEO consists of a circular aperture on the Solar Orbiter thermal shield. A spherical mirror rejects back the disk-light through the IEO. The experience built on all the previous space coronagraphs forces designers to dedicate a particular attention to the occulter optimization. Two breadboards were manufactured to perform occulter optimization measurements: BOA (Breadboard of the Occulting Assembly) and ANACONDA (AN Alternative COnfiguration for the Occulting Native Design Assembly). A preliminary measurement campaign has been carried on at the Laboratoire d’Astrophysique de Marseille. In this paper we describe BOA and ANACONDA designs, the laboratory set-up and the preliminary results.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".